HAPII

Human-centered,
Adaptive, and Personalized,
Information Interaction

About HAPII

The Human-centered, Adaptive, and Personalized Information Interaction Lab at Cal Poly Pomona researches novel solutions that aim to understand and support each individual user. We apply these techniques and solutions across a range of information access applications, including personalized web search, adaptive information visualization, and intelligent user interfaces.

Our research involves techniques and concepts from the fields of:

Human Computer Interaction

Information Retrieval & Visualization

Web & Data Science

Projects

Personalized Multilingual Search

Despite the unrelenting rise of global multilingualism (i.e. people being proficient in multiple languages), search systems typically tend to emphasize distinctions between languages, and often require multilingual users to conduct separate searches in order to retrieve results in more than one language. While research in Multilingual Search has made significant advances regarding the handling, retrieval, and automatic translation of content, there has been a distinct lack of human-centered research to better understand and support multilingual user behaviors, needs, preferences, and contexts.

The goal of our research is to run the first detailed lab experiments on multilingual search, as well as the first large-scale user behavior analyses of multilingual search users through large-scale online studies and search log analyses. Results from our research studies aim to drive the design and development of novel data-driven and personalized multilingual search systems that adapt the retrieval, composition, and presentation of multilingual information to each individual user’s language abilities, preferences, and search context.

Personalized Aggregated Search

A key challenge for search systems lies in their ability to retrieve and present the right information in the right form for each individual user’s needs, abilities, preferences, and context. In particular, a wide variety of content may be presented to each user for a given query (e.g. web results, news results, images, video, etc.), and search engines crucially need to decide what and how information should be presented. In recent years, a new search paradigm called Aggregated Search has emerged, which attempts to achieve search result page diversity by presenting search results from different information sources, so-called “verticals” in addition to the standard web results, on one result page.

However, this type of search system has seldom been personalized to individual users, as adaptation typically only focuses on the queries (e.g. query type, topic, etc.). The goal of our research is to develop the first personalized algorithms and interfaces for Aggregated Search, with the aim of providing tailored result pages for each individual user.

Personalized Information Visualization

Given the unprecedented amount of information now available to people, enterprises, and communities, it is becoming increasingly important to address the issue of information overload. In particular, in order to support daily data analysis and decision making activities, it is crucial to aid human operators, such as data scientists and data engineers, through effective data visualizations. Traditionally, such data visualization systems have followed a one-size-fits-all model, typically ignoring an individual user's needs, abilities, and preferences.

In our research, we aim to understand how different groups of people interact and synthesize information using different visualizations, and what types of visualizations aids may best help different groups of people understand the underlying data. Our research investigates this topic through detailed user studies capturing individual user behaviors and preferences, with the aim of creating more usable, effective, and personalized visualizations and visualization aids.

Personal Data Protection and Privacy

In order to better comply with EU GDPR requirements, Web site operators need to be aware of all the Cookies, Local Storage, and Flash Cookie usage of their Web Sites. In collaboration with Microsoft, we are working on a tool that, given a set of sites, generates a report based on the user data collected by those sites.

Lab Members

Lab Members

Dr. Ben Steichen
Dr. Ben Steichen
Faculty
Christian Becerra
Christian Becerra
Graduate Student
Carla Castillo
Carla Castillo
Undergraduate Student
Wei Hsuan Chen
Wei Hsuan Chen
Undergraduate Student
Jinjing Lee
Jinjing Lee
Undergraduate Student
Dimitri Pierre-Louis
Dimitri Pierre-Louis
Undergraduate Student
Kevin Scroggins
Kevin Scroggins
Undergraduate Student

Equipment

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The HAPII lab uses state-of-the-art usability and user experience research equipment, which enables us to perform detailed experiments and analyses of natural user behaviors and experiences.

Contact

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If you want to learn more about the HAPII lab, or if you are interested in research opportunities (undergraduate or graduate), please reach out to us!

  • Dep. of Computer Science, Cal Poly Pomona, 3801 West Temple Avenue, Pomona, California, 91768
  •       bsteichen [at] cpp.edu
  •       (909) 869-3437
  •       8-44